将 Pandas 数据框与公共列合并并为不匹配的值设置 NaN
要将两个具有公共列的PandasDataFrame合并，请使用该merge()函数并将ON参数设置为列名。要为不匹配的值设置NaN，请使用“how”参数并将其设置为left或right。这意味着向左或向右合并。
首先，让我们使用别名导入pandas库-
import pandas as pd
让我们创建DataFrame1-
dataFrame1 = pd.DataFrame(
{
"Car": ['BMW', 'Lexus', 'Audi', 'Mustang', 'Bentley', 'Jaguar'],"Units": [100, 150, 110, 80, 110, 90]
}
)让我们创建DataFrame2
dataFrame2 = pd.DataFrame(
{
"Car": ['BMW', 'Lexus', 'Tesla', 'Mustang', 'Mercedes', 'Jaguar'],"Reg_Price": [7000, 1500, 5000, 8000, 9000, 6000]
}
)现在，将DataFrames与公共列Car合并。左侧“”显示左侧DataFrame的所有值，并为来自第二个DataFrame的不匹配值设置NaN-
mergedRes = pd.merge(dataFrame1, dataFrame2, on ='Car', how ="left")
示例
以下是代码
import pandas as pd
# Create DataFrame1
dataFrame1 = pd.DataFrame(
{
"Car": ['BMW', 'Lexus', 'Audi', 'Mustang', 'Bentley', 'Jaguar'],"Units": [100, 150, 110, 80, 110, 90]
}
)
print("DataFrame1 ...\n",dataFrame1)
# Create DataFrame2
dataFrame2 = pd.DataFrame(
{
"Car": ['BMW', 'Lexus', 'Tesla', 'Mustang', 'Mercedes', 'Jaguar'],"Reg_Price": [7000, 1500, 5000, 8000, 9000, 6000]
}
)
print("\nDataFrame2 ...\n",dataFrame2)
# merge DataFrames with common column Car and "left" sets NaN for unmatched values from second DataFrame
mergedRes = pd.merge(dataFrame1, dataFrame2, on ='Car', how ="left")
print("\nMerged data frame with common column...\n", mergedRes)输出结果以下是代码-
DataFrame1 ...
Car Units
0 BMW 100
1 Lexus 150
2 Audi 110
3 Mustang 80
4 Bentley 110
5 Jaguar 90
DataFrame2 ...
Car Reg_Price
0 BMW 7000
1 Lexus 1500
2 Tesla 5000
3 Mustang 8000
4 Mercedes 9000
5 Jaguar 6000
Merged data frame with common column...
Car Units Reg_Price
0 BMW 100 7000.0
1 Lexus 150 1500.0
2 Audi 110 NaN
3 Mustang 80 8000.0
4 Bentley 110 NaN
5 Jaguar 90 6000.0